Cloud-based Machine Learning Techniques Implemented by Microsoft Azure for Designing Power Amplifiers

Jamshidi, Mohammad; Roshani, Saeed; Talla, Jakub; Sharifi-Atashgah, Maryam S.; Roshani, Sobhan; Peroutka, Zdeněk

doi:10.1109/uemcon53757.2021.9666639

Cited by 8 publications

(5 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In summary, microstrip components such as the suggested Global System for Mobile Communications (GSM) triplexer provide a range of advantages for sustainable IoT in smart grids and the metaverse. The most significant advantage of microstrip technology is that it only requires a two-layer board, with all components mounted on a single side, making it the most cost-effective RF circuit board solution [ 39 , 40 ]. As all components are located on the same surface, the use of vias when making connections is unnecessary, avoiding the introduction of unwanted capacitance or inductance.…”

Section: Discussionmentioning

confidence: 99%

A Super-Efficient GSM Triplexer for 5G-Enabled IoT in Sustainable Smart Grid Edge Computing and the Metaverse

Jamshidi

Yahya

Nouri

et al. 2023

Sensors

View full text Add to dashboard Cite

Global concerns regarding environmental preservation and energy sustainability have emerged due to the various impacts of constantly increasing energy demands and climate changes. With advancements in smart grid, edge computing, and Metaverse-based technologies, it has become apparent that conventional private power networks are insufficient to meet the demanding requirements of industrial applications. The unique capabilities of 5G, such as numerous connections, high reliability, low latency, and large bandwidth, make it an excellent choice for smart grid services. The 5G network industry will heavily rely on the Internet of Things (IoT) to progress, which will act as a catalyst for the development of the future smart grid. This comprehensive platform will not only include communication infrastructure for smart grid edge computing, but also Metaverse platforms. Therefore, optimizing the IoT is crucial to achieve a sustainable edge computing network. This paper presents the design, fabrication, and evaluation of a super-efficient GSM triplexer for 5G-enabled IoT in sustainable smart grid edge computing and the Metaverse. This component is intended to operate at 0.815/1.58/2.65 GHz for 5G applications. The physical layout of our triplexer is new, and it is presented for the first time in this work. The overall size of our triplexer is only 0.007 λg2, which is the smallest compared to the previous works. The proposed triplexer has very low insertion losses of 0.12 dB, 0.09 dB, and 0.42 dB at the first, second, and third channels, respectively. We achieved the minimum insertion losses compared to previous triplexers. Additionally, the common port return losses (RLs) were better than 26 dB at all channels.

show abstract

Section: Discussionmentioning

confidence: 99%

A Super-Efficient GSM Triplexer for 5G-Enabled IoT in Sustainable Smart Grid Edge Computing and the Metaverse

Jamshidi

Yahya

Nouri

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…Class-E PAs are widely used in several applications, such as biomedical [18], DC-DC power converter [19], rectifiers [20], RF heating [21], and wireless power transfer (WPT) [22,23] applications. The amplifiers can be realized in the forms of discrete [8][9][10][11][12] and integrated circuits (ICs) [24,25]. Additionally, photonic crystal fibers, which are used to achieve higher speeds and higher frequencies [26][27][28][29], can be used for amplifiers design [30,31].…”

Section: Power Supplymentioning

confidence: 99%

“…The power amplifier (PA) component plays an important role in the biomedical devices [2]. Among the PAs are the switching amplifiers, especially class-E type, which have a high efficiency and are desirable in biomedical applications [8][9][10][11][12]. The schematic of wireless power transfer with class-E PA using inductive coupling technique is illustrated in Figure 1.…”

Section: Introductionmentioning

confidence: 99%

A New Design Method for Class-E Power Amplifiers Using Artificial Intelligence Modeling for Wireless Power Transfer Applications

et al. 2022

Self Cite

View full text Add to dashboard Cite

This paper presents a new approach to simplify the design of class-E power amplifier (PA) using hybrid artificial neural-optimization network modeling. The class-E PA is designed for wireless power transfer (WPT) applications to be used in biomedical or internet of things (IoT) devices. Artificial neural network (ANN) models are combined with optimization algorithms to support the design of the class-E PA. In several amplifier circuits, the closed form equations cannot be extracted. Hence, the complicated numerical calculations are needed to find the circuit elements values and then to design the amplifier. Therefore, for the first time, ANN modeling is proposed in this paper to predict the values of the circuit elements without using the complex equations. In comparison with the other similar models, high accuracy has been obtained for the proposed model with mean absolute errors (MAEs) of 0.0110 and 0.0099, for train and test results. Moreover, root mean square errors (RMSEs) of 0.0163 and 0.0124 have been achieved for train and test results for the proposed model. Moreover, the best and the worst-case related errors of 0.001 and 0.168 have been obtained, respectively, for the both design examples at different frequencies, which shows high accuracy of the proposed ANN design method. Finally, a design of class-E PA is presented using the circuit elements values that, first, extracted by the analyses, and second, predicted by ANN. The calculated drain efficiencies for the designed class-E amplifiers have been obtained equal to 95.5% and 91.2% by using analyses data and predicted data by proposed ANN, respectively. The comparison between the real and predicted values shows a good agreement.

show abstract

“…In addition, speed sensorless IM drives have several advantages, including low cost, reduced complexity, and improved reliability [ 9 , 10 ]. Digital twins for IM drive systems are not commonly used for drive performance monitoring, health diagnostics, state optimization, and risk evaluation at different levels, including the entire system, subsystems, specific components, and others [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

Digital Twin Model of Electric Drives Empowered by EKF

Ebadpour

Jamshidi

Talla

et al. 2023

Sensors

Self Cite

View full text Add to dashboard Cite

Digital twins, a product of new-generation information technology development, allows the physical world to be transformed into a virtual digital space and provide technical support for creating a Metaverse. A key factor in the success of Industry 4.0, the fourth industrial revolution, is the integration of cyber–physical systems into machinery to enable connectivity. The digital twin is a promising solution for addressing the challenges of digitally implementing models and smart manufacturing, as it has been successfully applied for many different infrastructures. Using a digital twin for future electric drive applications can help analyze the interaction and effects between the fast-switching inverter and the electric machine, as well as the system’s overall behavior. In this respect, this paper proposes using an Extended Kalman Filter (EKF) digital twin model to accurately estimate the states of a speed sensorless rotor field-oriented controlled induction motor (IM) drive. The accuracy of the state estimation using the EKF depends heavily on the input voltages, which are typically supplied by the inverter. In contrast to previous research that used a low-precision ideal inverter model, this study employs a high-performance EKF observer based on a practical model of the inverter that takes into account the dead-time effects and voltage drops of switching devices. To demonstrate the effectiveness of the EKF digital twinning on the IM drive system, simulations were run using the MATLAB/Simulink software (R2022a), and results are compared with a set of actual data coming from a 4 kW three-phase IM as a physical entity.

show abstract

Cloud-based Machine Learning Techniques Implemented by Microsoft Azure for Designing Power Amplifiers

Cited by 8 publications

References 22 publications

A Super-Efficient GSM Triplexer for 5G-Enabled IoT in Sustainable Smart Grid Edge Computing and the Metaverse

A Super-Efficient GSM Triplexer for 5G-Enabled IoT in Sustainable Smart Grid Edge Computing and the Metaverse

A New Design Method for Class-E Power Amplifiers Using Artificial Intelligence Modeling for Wireless Power Transfer Applications

Digital Twin Model of Electric Drives Empowered by EKF

Contact Info

Product

Resources

About